A data engineering team is building a pipeline that ingests sensor data from IoT devices. They want to validate that each reading is within a plausible range (e.g., temperature between -50 and 150 degrees) and that timestamps are not in the future. They need to perform these checks as data is ingested. Which approach should they use?

Use AWS Glue DataBrew to create a recipe that filters out invalid readings before loading into S3.

Implement a Lambda function that validates each record and writes valid records to a Kinesis stream.

Configure an S3 bucket policy to reject objects with invalid data.

Use Amazon Athena to run a query that checks for invalid readings after the data is stored.

A retail company has merged data from two different systems into a single Amazon S3 data lake. The data engineering team notices that customer records from one system use 'customer_id' while the other uses 'cust_id', and some records have inconsistent state names (e.g., 'CA' vs 'California'). They need to investigate and resolve these inconsistencies. Which approach should they take?

Use Amazon Athena to run a one-time query that renames columns and updates state values.

Manually edit the CSV files in S3 to align the column names and state values.

Ignore the inconsistencies because the data is already in the data lake.

Use AWS Glue DataBrew to profile the data, identify mismatched schemas and values, and create recipes to standardize them.

In AWS Glue DataBrew, which step is required to apply a data quality rule to a dataset?

Create a recipe and add a custom step to check for null values.

Create a job and specify a transformation script.

Create a project and add a visualization.

Create a data quality ruleset and attach it to the dataset.

A data science team needs to build a model to predict customer churn. The dataset has 1 million records, with 5% churners. They want to create a sample that is representative of the overall population but also want to ensure that the rare churn class is adequately represented for training. Which sampling technique should they use?

Oversampling the minority class after stratified sampling

AWSCertified Data Engineer - Associate

Domain 3Objective 4

Task 3.4: Ensure Data Quality DEA-C01 Practice Questions (Page 1)

Part of the Content Domain 3: Data Operations and Support domain, which accounts for 22% of the DEA-C01 exam. AWS does not publish an official question count, but from its 130-minute exam (~50–85 total, ~11–19 in this domain), expect 3–5 from this objective — we provide 18 practice questions to prepare you well beyond it. (estimate)

18questions here

4free pages

5concepts

22%of the exam

Questions 1–5

1application · medium
A data engineering team is building a pipeline that ingests sensor data from IoT devices. They want to validate that each reading is within a plausible range (e.g., temperature between -50 and 150 degrees) and that timestamps are not in the future. They need to perform these checks as data is ingested. Which approach should they use?
Select an answer first
2application · medium
A retail company has merged data from two different systems into a single Amazon S3 data lake. The data engineering team notices that customer records from one system use 'customer_id' while the other uses 'cust_id', and some records have inconsistent state names (e.g., 'CA' vs 'California'). They need to investigate and resolve these inconsistencies. Which approach should they take?
Select an answer first
3foundation · easy
In AWS Glue DataBrew, which step is required to apply a data quality rule to a dataset?
Select an answer first
4expert · hard
A data science team needs to build a model to predict customer churn. The dataset has 1 million records, with 5% churners. They want to create a sample that is representative of the overall population but also want to ensure that the rare churn class is adequately represented for training. Which sampling technique should they use?
Select an answer first
5foundation · easy
A data engineer wants to sample every 10th record from a large dataset to create a smaller dataset for analysis. Which sampling technique is being used?
Select an answer first

Finished these 5 questions?

Review the revealed explanations, or continue through the curriculum.

Next 5 questions →Back to DEA-C01

Free Basic Practice is a study aid with revealable answers — not a scored exam. Examers.io is independent and not affiliated with or endorsed by AWS. “DEA-C01” is a trademark of its owner, used for identification only.

Task 3.4: Ensure Data Quality DEA-C01 Practice Questions (Page 1)

Questions 1–5

In AWS Glue DataBrew, which step is required to apply a data quality rule to a dataset?

A data engineer wants to sample every 10th record from a large dataset to create a smaller dataset for analysis. Which sampling technique is being used?

Keep studying — Content Domain 3: Data Operations and Support